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学者姓名：黄捷
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Abstract ：
This paper proposes an efficient fast-optimal balanced differential game (DG) approach to address the formation control problem in dynamic environments for networked multi-agent systems (MASs). Compared to existing receding horizon distributed differential game (RH-DDG) approaches, the proposed approach employs a two-layer game structure to balance optimality and real-time performance, with a focus on formation control, collision avoidance and obstacle avoidance. In the offline layer, the problem is converted into a distributed differential game (DDG) where each agent computes strategies using distributed information from locally neighboring agents. The strategy of each agent self-enforces a unique global Nash equilibrium (G-NE) with a strongly connected communication topology, providing an optimal reference trajectory for the online game. In the online layer, a receding horizon differential game with an event-trigger mechanism (RH-DGET) is presented to track the G-NE trajectory. Ego players are triggered to update online Nash strategies only when the event-triggering condition is satisfied, ensuring the real-time safety certificate. Rigorous proofs demonstrate that the online Nash strategies converge to the offline G-NE until the trigger ends, and a certain dwell time condition is given to prevent the Zeno behavior. Simulation results validate the effectiveness of the proposed approach. © 2025 World Scientific Publishing Company.
Keyword ：
Computation theory Computation theory Game theory Game theory Multi agent systems Multi agent systems Networked control systems Networked control systems
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| GB/T 7714 | Xue, Wenyan , Huang, Jie , Chen, Nan et al. Distributed Formation Control of Multi-Agent Systems: A Novel Fast-Optimal Balanced Differential Game Approach [J]. | Unmanned Systems , 2025 , 13 (1) : 211-231 . |
| MLA | Xue, Wenyan et al. "Distributed Formation Control of Multi-Agent Systems: A Novel Fast-Optimal Balanced Differential Game Approach" . | Unmanned Systems 13 . 1 (2025) : 211-231 . |
| APA | Xue, Wenyan , Huang, Jie , Chen, Nan , Chen, Yutao , Lin, Dingci . Distributed Formation Control of Multi-Agent Systems: A Novel Fast-Optimal Balanced Differential Game Approach . | Unmanned Systems , 2025 , 13 (1) , 211-231 . |
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This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking accuracy. Moreover, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.
Keyword ：
Adaptive integral surge line-of-sight Adaptive integral surge line-of-sight approximation approximation robotic fish robotic fish speed observer speed observer
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| GB/T 7714 | Li, Dongfang , Huang, Jie , Law, Rob et al. Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes [J]. | IEEE-CAA JOURNAL OF AUTOMATICA SINICA , 2025 , 12 (1) : 126-137 . |
| MLA | Li, Dongfang et al. "Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes" . | IEEE-CAA JOURNAL OF AUTOMATICA SINICA 12 . 1 (2025) : 126-137 . |
| APA | Li, Dongfang , Huang, Jie , Law, Rob , Xu, Xin , Zhu, Limin , Wu, Edmond Q. . Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes . | IEEE-CAA JOURNAL OF AUTOMATICA SINICA , 2025 , 12 (1) , 126-137 . |
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This paper proposes a leader-follower control method for multiple snake robot formation. Based on the simplified snake robot model, this work improves the traditional Serpenoid gait mode to a time-varying frequency form. Combined with the line-of-sight (LOS) method, a snake robot trajectory tracking controller is designed to enable the leader to track the desired trajectory at the ideal velocity. Then, the leader-follower following error system of a snake robot formation is established. In this framework, the follower can maintain a preset geometric position relationship with the leader to ensure the fast convergence of the formation location. Lyapunov's theory proves the stability of a snake robot formation error. Simulation and experimental results show that this strategy has the advantages of faster convergence speed and higher tracking accuracy than other current methods.
Keyword ：
Formation control Formation control Leader-follower Leader-follower Snake robot Snake robot Trajectory tracking Trajectory tracking
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| GB/T 7714 | Wang, Wu , Du, Zhihang , Li, Dongfang et al. Leader-follower method-based formation control for snake robots [J]. | ISA TRANSACTIONS , 2025 , 156 : 609-619 . |
| MLA | Wang, Wu et al. "Leader-follower method-based formation control for snake robots" . | ISA TRANSACTIONS 156 (2025) : 609-619 . |
| APA | Wang, Wu , Du, Zhihang , Li, Dongfang , Huang, Jie . Leader-follower method-based formation control for snake robots . | ISA TRANSACTIONS , 2025 , 156 , 609-619 . |
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针对目前卓越人才培养模式与市场需求不相符、培养体系与产业发展不匹配、人才质量与社会期望有差距等问题，提出构建共同体协同发展视域下的“五整合(整合共同体资源)+四提升(知识、能力、素养及身份认同)+三协同(小导师、校内外导师)+二共研(师资力量建设和教研教改项目)+一应用(数字技术应用)”人才培养模式，设计了基于数字技术的“外部环境-共同体-数字技术-学习者”及“学习-实践-评价-塑造”双重四螺旋卓越人才培养路径。对于推动卓越人才培养、提升人才培养质量具有一定的作用。
Keyword ：
人才培养 人才培养 共同体 共同体 数字赋能 数字赋能
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| GB/T 7714 | 陈东毅 , 黄捷 , 王武 et al. 共同体协同发展视域下数字赋能卓越人才培养探索 [J]. | 实验室研究与探索 , 2025 , 44 (05) : 164-168 . |
| MLA | 陈东毅 et al. "共同体协同发展视域下数字赋能卓越人才培养探索" . | 实验室研究与探索 44 . 05 (2025) : 164-168 . |
| APA | 陈东毅 , 黄捷 , 王武 , 陈建国 , 李玉榕 . 共同体协同发展视域下数字赋能卓越人才培养探索 . | 实验室研究与探索 , 2025 , 44 (05) , 164-168 . |
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In the paper, the formation control problem in unknown environments for networked multi-unmanned aerial vehicle systems (UAVSs) is resolved under a nonlinear differential game (NL-DDG) framework. The main challenge of this framework is how to obtain feedback Nash strategies, which typically overly rely on global information and cannot ensure the existence of Nash strategies in unknown environments. Toward this goal, we initially design collision avoidance rules to ensure the safety of each UAV. Subsequently, we utilize an inverse optimal control method to construct the NL-DDG that incorporates both formation control and collision avoidance costs, enabling the derivation of analytical forms of Nash strategies relying solely on local information and minimizing performance metrics. In addition, the existence of feedback Nash strategy can be guaranteed with an undirected and connected information topology, which represents the optimality for the UAVSs. Moreover, we analyze the stability of the closed-loop system. Finally, the simulation results validate the effectiveness of the proposed scheme. © 2025 World Scientific Publishing Company.
Keyword ：
Aircraft accidents Aircraft accidents Closed loop control systems Closed loop control systems Collision avoidance Collision avoidance Feedback Feedback Inverse problems Inverse problems Networked control systems Networked control systems Optimal control systems Optimal control systems Unmanned aerial vehicles (UAV) Unmanned aerial vehicles (UAV)
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| GB/T 7714 | Xue, Wenyan , Huang, Jie , Li, Zeyi et al. Formation Control with Feedback Nash Strategy for Multiple Unmanned Aerial Vehicles in Unknown Environments [J]. | Unmanned Systems , 2025 , 13 (4) : 1115-1122 . |
| MLA | Xue, Wenyan et al. "Formation Control with Feedback Nash Strategy for Multiple Unmanned Aerial Vehicles in Unknown Environments" . | Unmanned Systems 13 . 4 (2025) : 1115-1122 . |
| APA | Xue, Wenyan , Huang, Jie , Li, Zeyi , Xin, Bin . Formation Control with Feedback Nash Strategy for Multiple Unmanned Aerial Vehicles in Unknown Environments . | Unmanned Systems , 2025 , 13 (4) , 1115-1122 . |
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An intelligent policy iteration tracking control method is proposed for the tracking control problem with bounded time-varying disturbances. An adaptive disturbance compensator is designed to counteract the bounded disturbance and guarantee the validity of the Hamilton-Jacobi-Bellman (HJB) equation. An identifier network is proposed to estimate the unknown vehicle dynamics, and a new HJB equation is derived using the reconstructed identifier tracking error. An online optimal tracking control strategy for unmanned vehicles is obtained in the state of identifier estimation with the assistance of actor-critic network. Based on Lyapunov theory, it is demonstrated that the identifier tracking error, identifier approximation error and neural network weight errors are all semi-globally uniformly ultimately bounded, and the unmanned vehicle can achieve ideal tracking performance. Simulation results indicate that with a disturbance upper-bounded by 10.331 1 N, the tracking error converges to at least 0.054 8 m which exhibits better anti-interference performance. Compared with sliding mode control, tracking accuracy is improved by 40% and control cost is reduced by 22%. © 2025 Acta Simulata Systematica Sinica. All rights reserved.
Keyword ：
Magnetic levitation vehicles Magnetic levitation vehicles Optimal control systems Optimal control systems State estimation State estimation Time varying control systems Time varying control systems
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| GB/T 7714 | Huang, Jie . An Intelligent Tracking Control Method for Unmanned Vehicles with Time-varying Disturbances [J]. | Journal of System Simulation , 2025 , 37 (4) : 1063-1075 . |
| MLA | Huang, Jie . "An Intelligent Tracking Control Method for Unmanned Vehicles with Time-varying Disturbances" . | Journal of System Simulation 37 . 4 (2025) : 1063-1075 . |
| APA | Huang, Jie . An Intelligent Tracking Control Method for Unmanned Vehicles with Time-varying Disturbances . | Journal of System Simulation , 2025 , 37 (4) , 1063-1075 . |
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针对具有有界时变干扰的无人车辆跟踪控制问题,提出了一种策略迭代智能跟踪控制方法.通过设计自适应干扰消解器对外界干扰进行补偿,确保了哈密顿-雅克比-贝尔曼(Hamilton-Jacobi-Bellman,HJB)方程的有效性;通过设计标识符网络对未知车辆动力学进行估计,并利用重构的标识符跟踪误差推导出全新的HJB方程;借助演员-评论家网络,在线获得标识符估计状态下的无人车辆最优跟踪控制策略.基于李雅普诺夫理论,证明了标识符跟踪误差、标识符近似误差、神经网络权值误差均为半全局最终一致有界,无人车辆可以达到理想的跟踪性能.仿真结果表明:在上界为10.331 1 N的外界干扰影响下,该方法的跟踪误差至少收敛到了 0.054 8 m,具有良好的抗干扰性能,与滑模控制方法相比,跟踪精度提高了 40％,控制代价减少了 22％.
Keyword ：
无人车辆 无人车辆 时变扰动 时变扰动 标识符网络 标识符网络 策略学习 策略学习 跟踪控制 跟踪控制
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| GB/T 7714 | 黄捷 . 一种时变扰动下的无人车辆智能跟踪控制方法 [J]. | 系统仿真学报 , 2025 , 37 (4) : 1063-1075 . |
| MLA | 黄捷 . "一种时变扰动下的无人车辆智能跟踪控制方法" . | 系统仿真学报 37 . 4 (2025) : 1063-1075 . |
| APA | 黄捷 . 一种时变扰动下的无人车辆智能跟踪控制方法 . | 系统仿真学报 , 2025 , 37 (4) , 1063-1075 . |
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Cooperative trajectory planning of aerial-ground systems is a fundamental and challenging problem, which aims to leverage the aerial information to assist the ground tasks. Existing methods often suffer from suboptimal trajectories or computation burden. In this paper, we address cooperative trajectory planning of aerial-ground systems in which an unmanned ground vehicle (UGV) plans its local trajectory in real-time with the assistance of an unmanned aerial vehicle (UAV). Firstly, the UAV generates guidance trajectory using nonlinear model predictive control (NMPC), which considers the obstacle distribution density as a factor reflecting the coupling effect of multiple obstacles on the UGV, thereby avoiding local minima problem and improving the feasibility of the planned trajectory. Secondly, a null-space-based behavioral control (NSBC) framework is employed to merge the guidance trajectory into the UGV's own planned one as a task. Finally, an event triggering task supervisor is developed for the UGV to decide the priorities of all tasks, which reduces the switching frequency of task priorities brought by traditional rule-based task supervisors. Both simulation and experiment results show that the proposed approach has superior trajectory planning performance in terms of trajectory error, on-line computation time and the success rate of task execution.
Keyword ：
Aerial-ground systems Aerial-ground systems Behavioral control Behavioral control Model predictive control Model predictive control Trajectory planning Trajectory planning
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| GB/T 7714 | Huang, Jie , Chen, Jianfei , Zhang, Zhenyi et al. On Real-time Cooperative Trajectory Planning of Aerial-ground Systems [J]. | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS , 2024 , 110 (1) . |
| MLA | Huang, Jie et al. "On Real-time Cooperative Trajectory Planning of Aerial-ground Systems" . | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS 110 . 1 (2024) . |
| APA | Huang, Jie , Chen, Jianfei , Zhang, Zhenyi , Chen, Yutao , Lin, Dingci . On Real-time Cooperative Trajectory Planning of Aerial-ground Systems . | JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS , 2024 , 110 (1) . |
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This paper studies control strategies of intelligent vehicles at unsignalized intersections. By considering the interaction among multiple vehicles and communication disturbances, the problem is formulated as a robust differential game in which the controlled vehicle computes actions using disturbed information of locally neighboring vehicles. Both cooperative and non-cooperative differential game models are considered. The controlled vehicle optimizes its own cost in the non-cooperative game while coordinates its strategy with other vehicles to optimize a joint cost in the cooperative game. We show that the local optimal strategy of each intelligent vehicle defined by a single optimization problem converges to global robust Nash equilibrium in the non-cooperative game, and converges to the global robust Pareto-Nash equilibrium in the cooperative game. The effectiveness of the robust differential game method is verified by simulations under two scenarios. Results show that under the proposed differential game approach, vehicles pass through unsignalized intersections more quickly than methods using traditional discrete game approaches. In addition, vehicles can avoid colliding with each other and obstacles at the presence of communication disturbances.
Keyword ：
Costs Costs differential game differential game Differential games Differential games Games Games game theory game theory Nash equilibrium Nash equilibrium Optimal control Optimal control robust Nash equilibrium robust Nash equilibrium Unsignalized intersection Unsignalized intersection Vehicle dynamics Vehicle dynamics Vehicular ad hoc networks Vehicular ad hoc networks
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| GB/T 7714 | Huang, Jie , Wu, Zhihong , Xue, Wenyan et al. Non-Cooperative and Cooperative Driving Strategies at Unsignalized Intersections: A Robust Differential Game Approach [J]. | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2024 , 25 (8) : 9535-9549 . |
| MLA | Huang, Jie et al. "Non-Cooperative and Cooperative Driving Strategies at Unsignalized Intersections: A Robust Differential Game Approach" . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 25 . 8 (2024) : 9535-9549 . |
| APA | Huang, Jie , Wu, Zhihong , Xue, Wenyan , Lin, Dingci , Chen, Yutao . Non-Cooperative and Cooperative Driving Strategies at Unsignalized Intersections: A Robust Differential Game Approach . | IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS , 2024 , 25 (8) , 9535-9549 . |
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To address the challenges of significant changes in the field of view and complex spatiotemporal information in unmanned aerial vehicle aerial image target detection, a model for small object detection in aerial photography based on low dimensional image feature fusion is presented grounded on the YOLOv5(you only look once version 5) architecture. Coordinate attention is introduced to improve the inverted residuals of MobileNetV3, thereby increasing the spatial dimension information of images while reducing parameters of the model. The YOLOv5 feature pyramid network structure is improved to incorporate feature images from shallow networks. The ability of the model to represent low-dimensional effective information of images is enhanced, and consequently the detection accuracy of the proposed model for small objects is improved. To reduce the impact of complex background in the image, the parameter-free average attention module is introduced to focus on both spatial attention and channel attention. VariFocal Loss is adopted to reduce the weight proportion of negative samples in the training process. Experiments on VisDrone dataset demonstrate the effectiveness of the proposed model. The detection accuracy is effectively improved while the model complexity is significantly reduced. © 2024 Science Press. All rights reserved.
Keyword ：
Aerial photography Aerial photography Antennas Antennas Complex networks Complex networks Image enhancement Image enhancement Object detection Object detection Object recognition Object recognition
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| GB/T 7714 | Cai, Fenghuang , Zhang, Jiaxiang , Huang, Jie . Model for Small Object Detection in Aerial Photography Based on Low Dimensional Image Feature Fusion [J]. | Pattern Recognition and Artificial Intelligence , 2024 , 37 (2) : 162-171 . |
| MLA | Cai, Fenghuang et al. "Model for Small Object Detection in Aerial Photography Based on Low Dimensional Image Feature Fusion" . | Pattern Recognition and Artificial Intelligence 37 . 2 (2024) : 162-171 . |
| APA | Cai, Fenghuang , Zhang, Jiaxiang , Huang, Jie . Model for Small Object Detection in Aerial Photography Based on Low Dimensional Image Feature Fusion . | Pattern Recognition and Artificial Intelligence , 2024 , 37 (2) , 162-171 . |
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